Empirical analysis of the Laplace and neural tangent kernel reproducing kernel Hilbert space (RKHS)
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Aug 18, 2022 - Jupyter Notebook
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reproducing-kernel-hilbert-space
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This is the recent work of my on the importance and application of mathematical function around its Hilbert function theory on artificial intelligence algorithms. The main motivation was the desire of improving the convergence rate and learning rate of various learning algorithms via Generalized Gaussian Radial Basis Function.
deep-neural-networks
deep-learning
neural-network
machine-learning-algorithms
artificial-intelligence
image-recognition
support-vector-machine
kernel-regression
gaussian-process-regression
activation-functions
reproducing-kernel-hilbert-space
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Mar 13, 2024 - MATLAB
This research work is about Limited Data Acquisition for the real life physical experiment of fluid flow across cylinder based on Kernelized Extended Dynamic Mode Decomposition by incorporating Gaussian Random Matrix Theory and Laplacian Kernel Function Hilbert space.
julia-language
random-matrix-theory
dynamic-mode-decomposition
reproducing-kernel-hilbert-space
laplacian-kernel
koopman-operator-theory
gaussian-random-vector
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Mar 13, 2024 - Python
Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.
mmd
regularization
sampling
rkhs
gradient-flow
sampling-methods
f-divergence
wasserstein-gradient-flows
particle-flow
reproducing-kernel-hilbert-space
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Updated
Apr 3, 2024 - Python
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